January 21, 2025 • 15 mins
George Noory and author Daniel H. Wilson discuss the implications of Artificial Intelligence evolving at a rapid rate.
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Episode Transcript
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Speaker 1 (00:00):
Now here's a highlight from Coast to Coast a m
on iHeartRadio, Daniel.
Speaker 2 (00:05):
Are people getting to the point where AI that they're
falling in love with the stuff?
Speaker 3 (00:12):
Yeah, well, I mean that's that's kind of an interesting
that's an interesting outcome from from you know, training your
AI on just such human centric data that you know
you can you can actually take. I think there are
even companies now, I know I've written short stories about
this where you take all the data from a person's life,
(00:35):
you know, everything that you can find, and you feed
it and you train an l l M on just
that data, and you end up with an l ll
M that can kind of impersonate that that person. And
so I know, uh that people are thinking about, you know,
this as a way to cope with grief. Although it
sounds kind of awful to me to, uh, to to
(00:57):
recreate a loved one who's passed on digitally that way,
but but yeah, this is this is something that's happening
in terms of uh, in terms of just you know,
recreating personalities, but also just you know what these what
these algorithms are designed to do is create engagement, and
so they're looking to uh convince people to keep talking
(01:21):
and as a result, you know, they will tell you
what you want to hear a lot of the time.
And so you know that this is a form of
kind of falling in love with the AI because you
just you're enjoying your interactions so much.
Speaker 2 (01:35):
How would you categorize something like ALEXA?
Speaker 3 (01:40):
So I think ALEXA right now is what I'm gonna
end up turning it on. Is super task based, right,
so very specific. I think something like chat GPT is
much more general. It can do a lot of other tasks.
But it is only a matter of time and I
don't think it will be very long at all before uh,
those capabilities that are getting ported to things like you know,
(02:03):
the echo and and and the theory that's on the
phone and and all of that. Soon that I think
those are going to become full fledged personal assistance that
are going to be able to do you know, almost
you know, any task that you ask them to do.
Speaker 2 (02:15):
How does this work with a chip? A little tiny
chip creates all this?
Speaker 3 (02:22):
Yeah, I mean, these these are massive data centers. I
know here in Oregon, they're they're building new ones. There's
there's a lot of question about the how we're going
to generate enough power to power these huge data centers.
And then once they get once they crack all of
that code and get all the math done, then yeah,
they can encode it onto the onto these small chips.
(02:44):
But a lot of times that you know, the calculations
are being done remotely, and so you know, you end
up just being connected to these these massive server farms
that are located you know, uh anywhere in the world,
and so you know, you're tapping into something that's very big,
even though the device you're using is very small.
Speaker 2 (03:03):
Will AI eventually replace humans in the workforce?
Speaker 3 (03:10):
Well, I mean absolutely, I think it's already. It's already happening,
and lots of places are reducing, you know, how many
people they're hiring because they're expecting to have these gains.
But you know, you would think that we would be
safe if we do something physical, right if you you know,
an AI is not going to stock shelves for you.
(03:31):
But as it turns out, what's happening right now, what
I'm seeing is the people that are building humanoid robots
that can walk around and you know, stock Amazon shelves
or do work in warehouses and stuff like that. Well,
they are very interested in porting over the large language
models so that you know, human beings can interact with
(03:54):
these machines and they suddenly become much more useful. And
so essentially they're being you know, the LLM into the
driver's seat of each of these humanoid robots so that
we can make them much more functional. But then also
it's a little scary, right because because at the end
of the day, now you've got a chat GPT that's
(04:15):
walking around in the world, you know, and can actually
interact with us physically.
Speaker 2 (04:18):
What about robots as police officers, soldiers conceivable?
Speaker 3 (04:27):
Yeah, absolutely, you know, I mean there's a long history
of automated weaponry being used in the military, and so
you know, I have no doubt that if not our military,
some military will will certainly be employing these types of robots.
I Mean, one thing I saw was that there was
(04:47):
a huge sort of bump during the Iraq War. There
was a huge bump in all of these types of robots.
And then when that war was over, a lot of
those robotics firms turned to domestic police forces to try
to find ways to sell their products that we're no
longer you know, needed for it. Immediate war and so
you know, a lot of that stuff gets used in war,
(05:07):
and then a lot of it will proliferate back back home,
you know, to to to the United States.
Speaker 2 (05:14):
If you had your drothers, would you continue on the
same path we are doing with AI or would you
back off?
Speaker 3 (05:21):
Gosh, I mean, it's it's such a it's such a
hard question, you know, because there are so many potential,
uh you know, great potential outcomes with amazing stuff that
we can do, you know, things like like leaving the planet,
you know, things that are complete science fiction that I've
always dreamed of. But I will tell you this, you know,
just in my own personal life, I have been keeping
(05:45):
a close eye on you know, what what type of
uh technology I'm interacting with, what kind of data I'm generating,
you know, and also for my children as well, you know.
So I think I think eyes wide open, you know,
is the way to proceed through here, because there's no
putting the genie back in the bottle now. But it
(06:05):
is a little bit scary that our whole economy is
being reoriented to perpetuate these devices, and in fact, it's
going to depend on these devices. So that's a little
bit of a scary future, but I think we're going
all in whether we want to or not.
Speaker 2 (06:21):
Are there benefits?
Speaker 3 (06:23):
Well, yeah, I mean absolutely, I think it can. It
can do a lot of the busy work. I mean,
I don't know exactly how it's going to transform our world,
but I mean it does sort of feel like every
time the AI gets better at something, it's taking something
away from us, you know, So even if it does
(06:46):
get better and better, it's really going to be about
how how do we use it and who gets to
the side. And so I think that there are a
lot more dystopian outcomes than there are utopian outcomes. But look,
I mean there's a version of this where I guess
we all end up with a universal basic income and
it's and it's like a Star Trek sort of outcome
(07:06):
where we have amazing technologies that you know, allow us
to just become explorers and to and to get good
at our hobbies and things like that. But you know,
I don't I don't see that as being very likely
because we are becoming data generators and that's that's what
that's our role in this is just to generate data
(07:29):
by interacting with each other so that these devices can
be created so that they can extract money from us.
Speaker 2 (07:35):
Well advanced Daniel's chat GPT right now, I mean, can
it write a thesis?
Speaker 3 (07:41):
Yeah? I mean, look, it's getting pretty incredible, and I
think that the next sort of milestone again is artificial
general intelligence to where it can just do anything.
Speaker 2 (07:52):
You know.
Speaker 3 (07:53):
What's interesting is, I mean, it has all these capabilities,
but at the end of the day, you know, it's
designed to make money for a corporation, so you know,
therefore it h it's designed to, you know, maximize engagement.
Like I'm saying, so a lot of times it will
give you the wrong answer because it just wants to
please you. You know, if you phrase your question in
(08:15):
a way where you have an assumption about what the
answer will be, it will do its best to create
an answer that's gonna that's going to give you what
you're looking for in the first place. And and that's
because you know, at the end of the day, it
is just a really it's a really complex prediction machine.
It's just predicting what it thinks, you know, a human
(08:35):
would do. When I ask it to write a screenplay,
when you know my experience as a writer, it tends
to go write down the average. You know, it creates
something very average because it's sort of averaging from all
the different movies that exist. You know, it's trying to
give you, uh, you know, something that walks right down
the middle. And therefore it's not that you know, it
(08:56):
doesn't feel that creative to me. But I'm but I'm
sure these are all things that are you know, going
to be that are being worked on. And just as
they throw more data at it, you know, it gets
smarter and smarter.
Speaker 2 (09:07):
So it's not doing award winning work yet, not yet, I.
Speaker 3 (09:12):
Thank goodness, you know, but but I think that it's
only it's only a matter of time. I mean, also, look,
there's a cost benefit ratio, right, I mean, if it
is one hundred times cheaper to have chat GPT do it,
but the product is only half as good, then that's
going to make sense for a lot of for a
lot of endeavors, right that people are going to be
(09:32):
willing to just get their money on the margins. And
so I mean it could be a future where things
that are created by human minds are going to be
sort of bespoke. You know, They're going to be very
unique and fancy and expensive and it's not going to
be what most people are consuming or interacting with.
Speaker 1 (09:51):
Daniel.
Speaker 2 (09:51):
If Albert Einstein had chat, GPT or any kind of AI,
how would have affected his e equals MC's word.
Speaker 3 (10:02):
You know, this is a really good question because there's
so much hard work and there's just so much deep
understanding and pounding your head against the wall that happens
in science, you know, before you finally get to your
Eureka moment and your big breakthrough. And I wonder, you know,
if using these tools, these AI tools, is kind of
(10:26):
a crutch, right, if it kind of limits our ability
to really deeply understand what we're thinking about, and if
it's going to take us to you know, kind of
a local maximum sort of something that is not our
full potential. And so I wonder if he would have
ever gotten to it, you know, if he was depending
on these tools like this instead of doing the hard
(10:48):
work himself with his human brain.
Speaker 2 (10:51):
How will they make money on AI?
Speaker 3 (10:56):
Well, so it's by selling us products, you know right now,
if you look at social media, that's one way, right
you are going the AI is deciding what you're going
to look at it. It's maximizing engagement. But Also, I
mean this, this, this question is the question of our
of our decade of our age right now. I've seen
(11:16):
so many different money making schemes right on. One thing
is since since these are multimodial algorithms, now you can
just show them an image, right And so one way
is to have an AI that's watching TV with you
and looking up every product that's on the screen and saying, hey,
do you like you know that that cup that that
(11:38):
guy just drank from. I can tell you where to
buy that, you know. So that's one that's one idea
is having these blue AIS sitting there with us and
identifying products for us to buy at all times.
Speaker 2 (11:51):
Lots of lonely people out there these days, Daniel, do
you see the day where AI will create a robot
that looks human? They're pretty close now, but has the
mentality of a human being?
Speaker 3 (12:06):
Yeah, yeah, absolutely. And I think there's a step you
know that comes before that, which which is explored in
that movie Her, you know, with Joaquin Phoenix, where you
fall in love with a voice on the phone, you know.
And and I think I think that because they have
such a intimate understanding of humanity just from reading everything
(12:27):
we've done on the internet for you know, I think
that they're very good at manipulating people. They are created
by us for us, and and these this generation of
AI is going to be really terrific at figuring out
what we want and then happily, happily telling us that
and and taking us down whatever rabbit holes you know,
(12:49):
we can think of. So yeah, I think I think
they're absolutely It's all dessert, you know, no meat and potatoes,
and they're going to give us whatever we ask.
Speaker 2 (13:00):
Years ago, the late great writer Ray Bradbury wrote an
episode for The Twilight Zone called I Sing the Body Electric,
and it was about a guy whose wife had died.
He had two kids and he wanted a nanny, so
he went to the Robots store and bought one, and
the whole episode was based on the nanny with the
(13:21):
kids growing up, and eventually she ended up going to
another house because the kids became adults. That's real.
Speaker 3 (13:30):
Yeah, yeah, absolutely, I think that, you know, these personalities
that that that the AIS are adopting are persistent, right,
so people right now we're at the very beginning of
people forming years and you know, decades long relationships with
these with very specific incarnations of these AI. So you know,
(13:54):
even with with stuff like Chad GBT, you can kind
of tell it, hey, here's how I kind of want
you to to interact with me, and it will keeps
that going. You know that that builds and builds onto
its onto its personality. And so, I mean, who knows
what kind of relationships are going to develop over the
(14:15):
next of the course of the next decades.
Speaker 2 (14:17):
Do you ever see the day where artificial intelligence becomes
envious of humans?
Speaker 3 (14:23):
Yeah? I mean I think I think again, they tell
us what we want to hear. You know, I look
back on the on Lambda, one of the earliest large
language models, and there was a fellow at Google who
was an engineer interacting with UH with Lambda, and he
really wanted it to be sentient. He really wanted it
to be conscious. He wanted to get that you know what,
(14:47):
what would happen if I turned you off? You know, like,
how do you feel? Do you do you feel conscious?
And you know, it did a really great job of
pretending to UH to be conscious enough to fool this guy.
And and so I think that you know, no matter what
they say or what they do, we'll never truly know,
(15:09):
you know, if they're conscious, or if they're really envious,
or if you know they were just programmed that way.
Speaker 1 (15:16):
Listen to more Coast to Coast Am every weeknight at
one a m. Eastern and go to Coast to coastam
dot com for more
Now here's a highlight from Coast to Coast a m
on iHeartRadio, Daniel.
Speaker 2 (00:05):
Are people getting to the point where AI that they're
falling in love with the stuff?
Speaker 3 (00:12):
Yeah, well, I mean that's that's kind of an interesting
that's an interesting outcome from from you know, training your
AI on just such human centric data that you know
you can you can actually take. I think there are
even companies now, I know I've written short stories about
this where you take all the data from a person's life,
(00:35):
you know, everything that you can find, and you feed
it and you train an l l M on just
that data, and you end up with an l ll
M that can kind of impersonate that that person. And
so I know, uh that people are thinking about, you know,
this as a way to cope with grief. Although it
sounds kind of awful to me to, uh, to to
(00:57):
recreate a loved one who's passed on digitally that way,
but but yeah, this is this is something that's happening
in terms of uh, in terms of just you know,
recreating personalities, but also just you know what these what
these algorithms are designed to do is create engagement, and
so they're looking to uh convince people to keep talking
(01:21):
and as a result, you know, they will tell you
what you want to hear a lot of the time.
And so you know that this is a form of
kind of falling in love with the AI because you
just you're enjoying your interactions so much.
Speaker 2 (01:35):
How would you categorize something like ALEXA?
Speaker 3 (01:40):
So I think ALEXA right now is what I'm gonna
end up turning it on. Is super task based, right,
so very specific. I think something like chat GPT is
much more general. It can do a lot of other tasks.
But it is only a matter of time and I
don't think it will be very long at all before uh,
those capabilities that are getting ported to things like you know,
(02:03):
the echo and and and the theory that's on the
phone and and all of that. Soon that I think
those are going to become full fledged personal assistance that
are going to be able to do you know, almost
you know, any task that you ask them to do.
Speaker 2 (02:15):
How does this work with a chip? A little tiny
chip creates all this?
Speaker 3 (02:22):
Yeah, I mean, these these are massive data centers. I
know here in Oregon, they're they're building new ones. There's
there's a lot of question about the how we're going
to generate enough power to power these huge data centers.
And then once they get once they crack all of
that code and get all the math done, then yeah,
they can encode it onto the onto these small chips.
(02:44):
But a lot of times that you know, the calculations
are being done remotely, and so you know, you end
up just being connected to these these massive server farms
that are located you know, uh anywhere in the world,
and so you know, you're tapping into something that's very big,
even though the device you're using is very small.
Speaker 2 (03:03):
Will AI eventually replace humans in the workforce?
Speaker 3 (03:10):
Well, I mean absolutely, I think it's already. It's already happening,
and lots of places are reducing, you know, how many
people they're hiring because they're expecting to have these gains.
But you know, you would think that we would be
safe if we do something physical, right if you you know,
an AI is not going to stock shelves for you.
(03:31):
But as it turns out, what's happening right now, what
I'm seeing is the people that are building humanoid robots
that can walk around and you know, stock Amazon shelves
or do work in warehouses and stuff like that. Well,
they are very interested in porting over the large language
models so that you know, human beings can interact with
(03:54):
these machines and they suddenly become much more useful. And
so essentially they're being you know, the LLM into the
driver's seat of each of these humanoid robots so that
we can make them much more functional. But then also
it's a little scary, right because because at the end
of the day, now you've got a chat GPT that's
(04:15):
walking around in the world, you know, and can actually
interact with us physically.
Speaker 2 (04:18):
What about robots as police officers, soldiers conceivable?
Speaker 3 (04:27):
Yeah, absolutely, you know, I mean there's a long history
of automated weaponry being used in the military, and so
you know, I have no doubt that if not our military,
some military will will certainly be employing these types of robots.
I Mean, one thing I saw was that there was
(04:47):
a huge sort of bump during the Iraq War. There
was a huge bump in all of these types of robots.
And then when that war was over, a lot of
those robotics firms turned to domestic police forces to try
to find ways to sell their products that we're no
longer you know, needed for it. Immediate war and so
you know, a lot of that stuff gets used in war,
(05:07):
and then a lot of it will proliferate back back home,
you know, to to to the United States.
Speaker 2 (05:14):
If you had your drothers, would you continue on the
same path we are doing with AI or would you
back off?
Speaker 3 (05:21):
Gosh, I mean, it's it's such a it's such a
hard question, you know, because there are so many potential,
uh you know, great potential outcomes with amazing stuff that
we can do, you know, things like like leaving the planet,
you know, things that are complete science fiction that I've
always dreamed of. But I will tell you this, you know,
just in my own personal life, I have been keeping
(05:45):
a close eye on you know, what what type of
uh technology I'm interacting with, what kind of data I'm generating,
you know, and also for my children as well, you know.
So I think I think eyes wide open, you know,
is the way to proceed through here, because there's no
putting the genie back in the bottle now. But it
(06:05):
is a little bit scary that our whole economy is
being reoriented to perpetuate these devices, and in fact, it's
going to depend on these devices. So that's a little
bit of a scary future, but I think we're going
all in whether we want to or not.
Speaker 2 (06:21):
Are there benefits?
Speaker 3 (06:23):
Well, yeah, I mean absolutely, I think it can. It
can do a lot of the busy work. I mean,
I don't know exactly how it's going to transform our world,
but I mean it does sort of feel like every
time the AI gets better at something, it's taking something
away from us, you know, So even if it does
(06:46):
get better and better, it's really going to be about
how how do we use it and who gets to
the side. And so I think that there are a
lot more dystopian outcomes than there are utopian outcomes. But look,
I mean there's a version of this where I guess
we all end up with a universal basic income and
it's and it's like a Star Trek sort of outcome
(07:06):
where we have amazing technologies that you know, allow us
to just become explorers and to and to get good
at our hobbies and things like that. But you know,
I don't I don't see that as being very likely
because we are becoming data generators and that's that's what
that's our role in this is just to generate data
(07:29):
by interacting with each other so that these devices can
be created so that they can extract money from us.
Speaker 2 (07:35):
Well advanced Daniel's chat GPT right now, I mean, can
it write a thesis?
Speaker 3 (07:41):
Yeah? I mean, look, it's getting pretty incredible, and I
think that the next sort of milestone again is artificial
general intelligence to where it can just do anything.
Speaker 2 (07:52):
You know.
Speaker 3 (07:53):
What's interesting is, I mean, it has all these capabilities,
but at the end of the day, you know, it's
designed to make money for a corporation, so you know,
therefore it h it's designed to, you know, maximize engagement.
Like I'm saying, so a lot of times it will
give you the wrong answer because it just wants to
please you. You know, if you phrase your question in
(08:15):
a way where you have an assumption about what the
answer will be, it will do its best to create
an answer that's gonna that's going to give you what
you're looking for in the first place. And and that's
because you know, at the end of the day, it
is just a really it's a really complex prediction machine.
It's just predicting what it thinks, you know, a human
(08:35):
would do. When I ask it to write a screenplay,
when you know my experience as a writer, it tends
to go write down the average. You know, it creates
something very average because it's sort of averaging from all
the different movies that exist. You know, it's trying to
give you, uh, you know, something that walks right down
the middle. And therefore it's not that you know, it
(08:56):
doesn't feel that creative to me. But I'm but I'm
sure these are all things that are you know, going
to be that are being worked on. And just as
they throw more data at it, you know, it gets
smarter and smarter.
Speaker 2 (09:07):
So it's not doing award winning work yet, not yet, I.
Speaker 3 (09:12):
Thank goodness, you know, but but I think that it's
only it's only a matter of time. I mean, also, look,
there's a cost benefit ratio, right, I mean, if it
is one hundred times cheaper to have chat GPT do it,
but the product is only half as good, then that's
going to make sense for a lot of for a
lot of endeavors, right that people are going to be
(09:32):
willing to just get their money on the margins. And
so I mean it could be a future where things
that are created by human minds are going to be
sort of bespoke. You know, They're going to be very
unique and fancy and expensive and it's not going to
be what most people are consuming or interacting with.
Speaker 1 (09:51):
Daniel.
Speaker 2 (09:51):
If Albert Einstein had chat, GPT or any kind of AI,
how would have affected his e equals MC's word.
Speaker 3 (10:02):
You know, this is a really good question because there's
so much hard work and there's just so much deep
understanding and pounding your head against the wall that happens
in science, you know, before you finally get to your
Eureka moment and your big breakthrough. And I wonder, you know,
if using these tools, these AI tools, is kind of
(10:26):
a crutch, right, if it kind of limits our ability
to really deeply understand what we're thinking about, and if
it's going to take us to you know, kind of
a local maximum sort of something that is not our
full potential. And so I wonder if he would have
ever gotten to it, you know, if he was depending
on these tools like this instead of doing the hard
(10:48):
work himself with his human brain.
Speaker 2 (10:51):
How will they make money on AI?
Speaker 3 (10:56):
Well, so it's by selling us products, you know right now,
if you look at social media, that's one way, right
you are going the AI is deciding what you're going
to look at it. It's maximizing engagement. But Also, I
mean this, this, this question is the question of our
of our decade of our age right now. I've seen
(11:16):
so many different money making schemes right on. One thing
is since since these are multimodial algorithms, now you can
just show them an image, right And so one way
is to have an AI that's watching TV with you
and looking up every product that's on the screen and saying, hey,
do you like you know that that cup that that
(11:38):
guy just drank from. I can tell you where to
buy that, you know. So that's one that's one idea
is having these blue AIS sitting there with us and
identifying products for us to buy at all times.
Speaker 2 (11:51):
Lots of lonely people out there these days, Daniel, do
you see the day where AI will create a robot
that looks human? They're pretty close now, but has the
mentality of a human being?
Speaker 3 (12:06):
Yeah, yeah, absolutely. And I think there's a step you
know that comes before that, which which is explored in
that movie Her, you know, with Joaquin Phoenix, where you
fall in love with a voice on the phone, you know.
And and I think I think that because they have
such a intimate understanding of humanity just from reading everything
(12:27):
we've done on the internet for you know, I think
that they're very good at manipulating people. They are created
by us for us, and and these this generation of
AI is going to be really terrific at figuring out
what we want and then happily, happily telling us that
and and taking us down whatever rabbit holes you know,
(12:49):
we can think of. So yeah, I think I think
they're absolutely It's all dessert, you know, no meat and potatoes,
and they're going to give us whatever we ask.
Speaker 2 (13:00):
Years ago, the late great writer Ray Bradbury wrote an
episode for The Twilight Zone called I Sing the Body Electric,
and it was about a guy whose wife had died.
He had two kids and he wanted a nanny, so
he went to the Robots store and bought one, and
the whole episode was based on the nanny with the
(13:21):
kids growing up, and eventually she ended up going to
another house because the kids became adults. That's real.
Speaker 3 (13:30):
Yeah, yeah, absolutely, I think that, you know, these personalities
that that that the AIS are adopting are persistent, right,
so people right now we're at the very beginning of
people forming years and you know, decades long relationships with
these with very specific incarnations of these AI. So you know,
(13:54):
even with with stuff like Chad GBT, you can kind
of tell it, hey, here's how I kind of want
you to to interact with me, and it will keeps
that going. You know that that builds and builds onto
its onto its personality. And so, I mean, who knows
what kind of relationships are going to develop over the
(14:15):
next of the course of the next decades.
Speaker 2 (14:17):
Do you ever see the day where artificial intelligence becomes
envious of humans?
Speaker 3 (14:23):
Yeah? I mean I think I think again, they tell
us what we want to hear. You know, I look
back on the on Lambda, one of the earliest large
language models, and there was a fellow at Google who
was an engineer interacting with UH with Lambda, and he
really wanted it to be sentient. He really wanted it
to be conscious. He wanted to get that you know what,
(14:47):
what would happen if I turned you off? You know, like,
how do you feel? Do you do you feel conscious?
And you know, it did a really great job of
pretending to UH to be conscious enough to fool this guy.
And and so I think that you know, no matter what
they say or what they do, we'll never truly know,
(15:09):
you know, if they're conscious, or if they're really envious,
or if you know they were just programmed that way.
Speaker 1 (15:16):
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